Enterprise cost management method and system based on big data

Abstract

The invention provides an enterprise cost management method and system based on big data, and relates to the technical field of enterprise cost management. The method comprises the following steps: continuously obtaining department work task data, carrying out conversion rate analysis based on output value profit, and forming department production efficiency data; historical human resource data of a department is collected, and human efficiency analysis is carried out to form existing human efficiency data of the department; performing manpower demand analysis according to the department production efficiency data and the department existing manpower efficiency data to form manpower demand analysis data; and obtaining department dynamic manpower demand information, and establishing department manpower demand data in combination with the manpower demand analysis data. According to the method, the demand condition of an enterprise department for human resources can be determined more accurately, the human structure can be optimized while sufficient human resources are ensured, the enterprise can perform cost management based on the human resources more reasonably, and the effects of reducing cost and creating income are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise cost management. Specifically, it relates to a method and system for enterprise cost management based on big data. Background Art

[0002] With the development of big data technology, more and more industries have achieved significant improvements in efficiency, technology, etc. through the application of big data technology, promoting social development. Human resources, as an important part of an enterprise, the control of human resources can more cost-effectively achieve the efficient operation of the enterprise. Of course, for human resources, there are many data that are difficult to quantify during management, and thus it is impossible to more accurately manage human resources.

[0003] Most of these difficult-to-quantify data come from complex data distributions and data forms, such as the quantitative statistics of work tasks, the reasonable determination of personnel efficiency, etc. However, with the application of big data technology, it is possible to more deeply monitor and count the operations of human resources, and then achieve the reasonable statistical quantification of those difficult-to-quantify data, providing help for the management of human resources. However, how to conduct reasonable human resource management after obtaining these data to ensure that the enterprise has sufficient and appropriate human resources and then achieve the effective management and control of enterprise costs is a problem worthy of consideration.

[0004] Therefore, designing a method and system for enterprise cost management based on big data, through the quantification of operation efficiency and operation content related to human resources for reasonable comparative analysis and processing, more accurately determining the demand for human resources in enterprise departments, ensuring sufficient human resources while also optimizing the human resource structure, enabling the enterprise to more reasonably conduct cost management based on human resources to achieve the effect of cost reduction and revenue increase, is an urgent problem to be solved at present. Summary of the Invention

[0005] The object of the present invention is to provide a big data-based enterprise cost management method. By obtaining the work task data of departments, extracting the efficiency data of departments in terms of output value and profit for the work task data, and using the historical data of department human resources to determine the operation efficiency of different personnel, on this basis, the matching analysis of the existing personnel operation efficiency and the department output value and profit efficiency is carried out to determine the manpower demand situation of the department, so as to provide a reasonable and accurate reference for the enterprise to carry out human resources planning for the department. At the same time, a reasonable demand analysis is carried out on the real-time human resources demand proposed by the department, so that when carrying out human resources planning, the specific demand situation of the required human resources can be determined more reasonably. Compared with the traditional human resources demand analysis, after combining the quantitative data related to human resources collected by big data, the specific situation of human resources demand can be determined more accurately and reasonably, greatly optimizing and improving the matching degree of the enterprise in terms of manpower demand, and enabling the enterprise to achieve the effect of cost reduction and efficiency increase in cost management through human resources.

[0006] The object of the present invention is also to provide a big data-based enterprise cost management system, which is an organic whole that can obtain department work task data through configuration for output value-profit conversion rate analysis, and combine human efficiency data for human demand optimization analysis to complete the reasonable control and management of human demand, greatly improving the efficiency and rationality of enterprise cost management through human resources management, effectively ensuring that the enterprise manages its costs through reasonable control of human resources, and enabling the enterprise to achieve the effect of reasonable cost reduction and efficiency increase in human resources.

[0007] In the first aspect, the present invention provides a big data-based enterprise cost management method, including: continuously obtaining department work task data, performing conversion rate analysis based on output value and profit to form department production efficiency data; collecting department historical human resources data and performing human efficiency analysis to form department existing human efficiency data; performing human demand analysis based on the department production efficiency data and the department existing human efficiency data to form human demand analysis data; obtaining department dynamic human demand information and establishing department human demand data in combination with the human demand analysis data.

[0008] In the present invention, the system extracts efficiency data of the department in terms of output value and profit by obtaining the work task data of the department and targeting the work task data. At the same time, it determines the operation efficiency of different human resources by using the historical data of the department's human resources. On this basis, it conducts a matching analysis of the current human operation efficiency and the department's output value and profit efficiency, determines the human resource demand situation of the department, and thus provides a reasonable and accurate reference for the enterprise to carry out human resource planning for the department. At the same time, it conducts a reasonable demand analysis on the human resource demands proposed by the department in real time, and then can more reasonably determine the specific demand situation of the required human resources when carrying out human resource planning. Compared with the traditional human resource demand analysis, after combining the quantitative data related to human resources collected by the Internet of Things, it can more accurately and reasonably determine the specific situation of human resource demand, greatly optimizing and improving the matching degree of the enterprise in terms of human resource demand, and enabling the enterprise to achieve the effect of cost reduction and efficiency increase.

[0009] As a possible implementation method, continuously obtain the work task data of the department, conduct a conversion rate analysis based on output value and profit, and form the production efficiency data of the department, including: setting a production efficiency analysis period, continuously obtaining the work task data of the majority of the department within the production efficiency analysis period, and forming the department's periodic production efficiency data; extracting the production task volume information in the department's periodic production efficiency data, and conducting a task volume change analysis to form the department's periodic task volume change data; extracting the production output value information in the department's periodic production efficiency data, and conducting an output value efficiency analysis to form the department's periodic output value efficiency data; extracting the production profit information in the department's periodic production efficiency data, and conducting a profit efficiency analysis to form the department's periodic profit efficiency data.

[0010] In the present invention, for the demand analysis of the department's human resources, it is necessary to consider the competence of the department's current human resources in terms of work ability. The competence of the department's human resources in work can be quantified by the workload completed by the human resources, but the quantification of the workload alone cannot accurately explain the current situation of human resources. On the one hand, because the quantification of the workload is only the objectively existing business level and not the ability manifestation of the subjective initiative of the human resources. On the other hand, the workload only reflects the speed of the human resources in terms of completion efficiency. For human resources, what is more important for the enterprise to obtain human resources is to maximize the benefits by using human resources. Therefore, when considering the allocation of human resources, it is necessary to comprehensively consider the output value and profit generated by the completed workload. Therefore, the department's production efficiency data needs to include the output value and profit situations created by the department's human resources. Of course, the higher the efficiency obtained for the output value and profit, the better the utilization rate of the human resources or the operation efficiency of the human resources. This kind of side reflection of human resources more quantitatively determines the current human resource situation of the department and is the data basis for subsequent human resource demand analysis.

[0011] As a possible implementation, extract the production task volume information from the department cycle production efficiency data, perform an analysis of the change in task volume, and form the department cycle task volume change data, including: determining the data volume processed within different production efficiency analysis cycles to form the department cycle task data volume; arranging the department cycle task data volume in chronological order to form the task volume cycle change data.

[0012] In the present invention, the workload is the basis of the human resource operation efficiency. Therefore, it is considered to first obtain the workload of the operation. Here, two aspects are considered for the quantification of the workload. On the one hand, which method is used to reasonably quantify the workload, and on the other hand, since the workload of the department is continuous, how to perform a reasonable quantitative analysis in the time dimension to make the analysis feasible. Here, for the quantification of the workload, the data volume to be formed by the work tasks is used to reflect it. After all, for the workload, different types of work and the same operation content will have different work content forms. Considering that under the Internet of Things, the operation data can be efficiently and accurately collected, and thus obtaining the data volume corresponding to the workload has a good quantification representation. For the feasibility of the quantitative analysis, considering that the analysis of human resource requirements is a data closely related to the time parameter, it is necessary to also quantify the workload based on the time dimension. At the same time, the acquisition of the workload has a certain degree of task periodicity, that is, under the project task, the workload has a certain definite value, and the completion of the project task also has a periodicity. Therefore, performing periodic quantification of the task volume based on the cycle characteristics of the project task is beneficial to subsequent analysis and processing. Of course, since the cycle times presented by different task projects are not highly consistent, it is also necessary to determine a reasonable cycle duration based on the actual situation during the periodic division to ensure a more reasonable workload division or to avoid unreasonable splitting of the work tasks based on the task workload.

[0013] As a possible implementation, extract the production output value information from the department cycle production efficiency data, perform an output value efficiency analysis, and form the department cycle output value efficiency data, including: taking the project as a unit, determining the project output value of different projects in the department cycle production efficiency data According to the department cycle task data volume, determine the project task data volume q of different projects within the corresponding production efficiency analysis cycle n and the total project task data volume of different projects n represents the numbers of different projects within the production efficiency analysis cycle; according to the project output value of different projects corresponding to the production efficiency analysis cycle the project task data volume q n and the total project task data volume determine the department cycle output value q corresponding to the production efficiency analysis cycle all, where Arrange the department's periodic output value q in chronological order all , and perform function fitting to form the department's periodic output value change function Q(t).

[0014] In the present invention, the output value efficiency mainly refers to the magnitude of the output value obtained by the department when expending human resources, and the magnitude of the output value corresponds to each task. Therefore, it is reasonable and accurate to analyze the output value efficiency based on tasks in different cycles. Considering that not all tasks can be completed within the corresponding production efficiency analysis cycle, it is necessary to reasonably determine the workload within each production efficiency cycle, especially the workload formed by the department on different projects, so as to accurately determine the overall acquisition situation of the output value within the cycle based on the project output value.

[0015] As a possible implementation method, extract the production profit information from the department's periodic production efficiency data, and perform profit efficiency analysis to form the department's periodic profit efficiency data, including: taking the project as a unit, determining the project profit of different projects in the department's periodic production efficiency data According to the project profit of different projects corresponding to the production efficiency analysis cycle The project task data volume q n And the total project task data volume Determine the department's periodic profit k corresponding to the production efficiency analysis cycle all , where Arrange the department's periodic profit k in chronological order all , and perform function fitting to form the department's periodic profit change function K(t).

[0016] In the present invention, similarly, for the production profit efficiency, it is also determined based on the profit magnitude obtained corresponding to the workload completed within the production cycle, so as to more reasonably and accurately reflect the revenue generation situation of the department when using human resources.

[0017] As a possible implementation method, collect the department's historical human resource data, and perform human efficiency analysis to form the department's current human efficiency data, including: setting the human efficiency analysis cycle, extracting the data volume completion rate of different humans in different projects from the department's historical human resource data; according to the data volume completion rate of different humans in different projects, determine the average human production efficiency a of each human m , where m represents the number of different humans currently in the department.

[0018] In the present invention, it can be understood that for different operators, due to their own or other reasons, there will be differences in production efficiency. At the same time, for different projects, the difficulty level of the projects will also affect the operation efficiency of the manpower. Therefore, the work efficiency of the manpower can be accurately determined through the manpower data collected within the analysis period, and the determined value is the average operation efficiency of different manpower, which is more representative and reasonable.

[0019] As a possible implementation method, based on the department production efficiency data and the existing manpower efficiency data of the department, manpower demand analysis is carried out to form manpower demand analysis data, including: according to the periodic change data of the task volume and the average manpower production efficiency a of different manpower m , apparent manpower demand analysis is carried out to form apparent manpower demand information; according to the apparent manpower demand information, and in combination with the department periodic output value change function Q(t) and the department periodic profit change function K(t), essential manpower demand analysis is carried out to form essential manpower demand information.

[0020] In the present invention, after obtaining the operation efficiency of the human resources and the output value efficiency and profit efficiency generated after the task operations carried out by the department, the matching analysis of the human resources and the task status to be completed can be carried out. Of course, the processing situation of the workload can naturally quickly determine the preliminary situation of the human resources, and on this basis, further analysis is carried out to determine the specific human resources demand situation.

[0021] As a possible implementation method, according to the periodic change data of the task volume and the average manpower production efficiency a of different manpower m , apparent manpower demand analysis is carried out to form apparent manpower demand information, including: according to the average manpower production efficiency a of different manpower m and the cycle duration T of different production efficiency analysis cycles i , the department competent data volume corresponding to the production efficiency analysis cycle is determined Among them, i represents the number of different production efficiency analysis cycles; according to the department cycle task data volume and the corresponding department competent data volume corresponding to different production efficiency analysis cycles the apparent task data margin corresponding to different production efficiency analysis cycles is determined Set the threshold α of the apparent manpower demand cycle number. According to different apparent task data margins the following apparent manpower demand analysis is carried out: if there are α production efficiency analysis cycles that are continuous in the time dimension sequence and all satisfy the corresponding apparent task data margin not less than the average manpower production efficiency a mThe total production volume of the minimum manpower within the corresponding production efficiency analysis period forms the apparent manpower shortage information; if there are no α consecutive production efficiency analysis periods in the time dimension sequence that all meet the corresponding apparent task data surplus not less than the average production efficiency a of the manpower m The total production volume of the minimum manpower within the corresponding production efficiency analysis period forms the apparent manpower sufficient information.

[0022] In the present invention, the preliminary, i.e., the apparent human resource demand situation mainly examines whether the human resources of the current department can complete the given task workload within the period, which is the primary condition for forming the human resource demand. After all, only when the task operation cannot be completed within the specified time, additional human resources are needed for supplementation. Therefore, the difference between the task workload and the task volume that the manpower can generally complete represents the magnitude of the human resource demand to a certain extent. This demand is judged by setting a reasonable threshold. After all, a temporary increase in the task volume will not affect the current human resource allocation, so this special change in the task workload needs to be excluded.

[0023] As a possible implementation manner, according to the apparent manpower demand information, and in combination with the department cycle output value change function Q(t) and the department cycle profit change function K(t), the essential manpower demand analysis is carried out to form the essential manpower demand information, including: when the apparent manpower demand information is the apparent manpower shortage information, a trend synchronization range A is set, and according to the department cycle output value change function Q(t) and the department cycle profit change function K(t), the following essential manpower demand analysis is carried out: according to the department cycle output value change function Q(t) and the department cycle profit change function K(t), the non-effective conversion economy F(t) is determined, where F(t)=Q'(t)-K'(t), Q'(t) represents the derivative of the department cycle output value change function Q(t) in the time dimension, and K'(t) represents the derivative of the department cycle profit change function K(t) in the time dimension; if the non-effective conversion economy F(t) satisfies F(t)∈A, the essential manpower shortage information is formed; if the non-effective conversion economy F(t) does not satisfy F(t)∈A, the essential manpower sufficient information is formed.

[0024] In the present invention, if the workload of the tasks to be completed within the workload analysis period exceeds the sum of the workloads processed by all human resources in the department and also exceeds the workload of the human with the lowest work efficiency in the department, it indicates that the continuously excessive task workload has reached or even exceeded the task workload that can be completed by a single individual, and the current human resources cannot meet the demand for increased workload. Therefore, it is necessary to have essential human resources. By determining the difference derivative of the output value efficiency and the profit efficiency, it is analyzed whether the change in profit is consistent with the change in output value. If the change in profit is consistent with the change in output value, it indicates that the department can achieve good profit growth, so there is no shortage of human resources. In this case, the task workload within the period exceeding the task workload that can be completed by all the human resources in the department only indicates that the optimization of task workload processing can be further carried out, that is, the reasonable allocation of human resources. This allocation can be reflected in the improvement of human processing efficiency or in the optimization of task workload. Of course, if the change in profit is not consistent with the change in output value, it means that no corresponding income has been obtained in terms of benefits after investing human resources. Therefore, it can be considered that the lack of human resources causes the core content of the task to be unable to be completed, and in this case, an increase in human resources is required.

[0025] Second, the present invention provides an enterprise cost management system based on big data, which is configured to: continuously obtain department work task data, conduct conversion rate analysis based on output value and profit, and form department production efficiency data; collect department historical human resource data, and conduct human efficiency analysis to form department current human efficiency data; according to the department production efficiency data and the department current human efficiency data, conduct human resource demand analysis to form human resource demand analysis data; obtain department dynamic human resource demand information, and combine it with the human resource demand analysis data to establish department human resource demand data.

[0026] In the present invention, an organic whole configured to obtain department work task data for output value and profit conversion rate analysis and combine human efficiency data for human resource demand optimization analysis to complete the reasonable control and management of human resource demand greatly improves the efficiency and rationality of enterprise cost management through human resource management, effectively ensuring that the enterprise manages its costs through reasonable control of human resources, and enabling the enterprise to achieve the effect of reasonable cost reduction and efficiency increase in human resources.

[0027] The beneficial effects of the enterprise cost management method and system based on big data provided by the present invention are as follows:

[0028] This method obtains the work task data of departments, extracts the efficiency data of departments in terms of output value and profit for the work task data, and determines the operation efficiency of different employees by using the historical data of department human resources. On this basis, it conducts a matching analysis of the current employee operation efficiency and the department output value and profit efficiency, determines the human resource requirements of the department, and thus provides a reasonable and accurate reference for the enterprise to carry out human resource planning for the department. At the same time, it conducts a reasonable demand analysis of the human resource requirements promptly proposed by the department, and can more reasonably determine the specific requirements of the human resources needed when carrying out human resource planning. Compared with the traditional human resource demand analysis, after combining the quantitative data related to human resources collected by big data, it can more accurately and reasonably determine the specific situation of human resource requirements, greatly optimizing and improving the matching degree of the enterprise in terms of human resource demand, and enabling the enterprise to achieve the effect of cost reduction and efficiency increase in cost management through human resources.

[0029] This system can, through configuration, obtain the department work task data for analysis of the output value-profit conversion rate, and combine the human efficiency data for optimized analysis of human resource requirements to complete an organic whole for the reasonable control and management of human resource requirements, greatly improving the efficiency and rationality of the enterprise's cost management through human resource management, effectively ensuring that the enterprise manages its costs through reasonable control of human resources, and enabling the enterprise to achieve the effect of reasonable cost reduction and efficiency increase in human resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative efforts.

[0031] Figure 1 It is a flowchart of the steps of the enterprise cost management method based on big data provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.

[0033] With the development of big data technology, more and more industries have applied big data technology to achieve significant improvements in efficiency, technology, etc., promoting social development. Human resources, as an important part of an enterprise, the control of human resources can more cost-effectively achieve the efficient operation of the enterprise. Of course, for human resources, there will be a lot of data that is difficult to quantify during management, and thus it is impossible to more accurately manage human resources.

[0034] Most of these difficult-to-quantify data come from complex data distributions and data forms, such as the quantitative statistics of work tasks and the reasonable determination of personnel efficiency. However, with the application of big data technology, the operations of human resources can be more deeply monitored and statistically analyzed, and then the reasonable statistical quantification of those difficult-to-quantify data can be achieved, providing help for the management of human resources. However, how to conduct reasonable human resource management after obtaining these data to ensure that the enterprise has sufficient and appropriate human resources and then achieve the effective management and control of enterprise costs is a question worthy of consideration.

[0035] Reference Figure 1 In view of this, the embodiments of the present invention provide an enterprise cost management method based on big data. This method obtains the work task data of departments, extracts the efficiency data of departments in terms of output value and profit for the work task data, and at the same time determines the operation efficiency of different human resources by using the historical data of department human resources. On this basis, the matching analysis of the current human resource operation efficiency and the department output value and profit efficiency is carried out to determine the human resource demand situation of the department, and then provide reasonable and accurate reference for the enterprise to carry out human resource planning for the department. At the same time, a reasonable demand analysis is carried out on the human resource demands proposed by the department in real time, and then the specific demand situation of the required human resources can be more reasonably determined when carrying out human resource planning. Compared with the traditional human resource demand analysis, after combining the quantitative data related to human resources collected by big data, the specific situation of human resource demand can be more accurately and reasonably determined, greatly optimizing and improving the matching degree of the enterprise in terms of human resource demand, and enabling the enterprise to achieve the effect of cost reduction and efficiency increase in cost management through human resources.

[0036] The enterprise cost management method based on big data includes the following specific steps:

[0037] S1: Continuously obtain the work task data of departments, conduct conversion rate analysis based on output value and profit, and form department production efficiency data.

[0038] Continuously obtain the department's work task data, conduct a conversion rate analysis based on output value and profit, and form the department's production efficiency data, including: setting the production efficiency analysis period, continuously obtaining the work task data of the majority of departments within the production efficiency analysis period, and forming the department's periodic production efficiency data; extracting the production task volume information from the department's periodic production efficiency data, and conducting an analysis of the change in task volume to form the department's periodic task volume change data; extracting the production output value information from the department's periodic production efficiency data, and conducting an output value efficiency analysis to form the department's periodic output value efficiency data; extracting the production profit information from the department's periodic production efficiency data, and conducting a profit efficiency analysis to form the department's periodic profit efficiency data.

[0039] The analysis of the department's human resource requirements necessarily requires considering the competence of the department's current human resources in terms of work ability. The competence of the department's human resources in work can be quantified by the workload completed by the personnel, but simply quantifying the workload cannot accurately describe the current situation of human resources. On the one hand, the quantification of the workload is only the objectively existing business level and does not reflect the ability of human subjective initiative. On the other hand, the workload only reflects the speed of human efficiency in completion. For human resources, what is more important for an enterprise to obtain human resources is to maximize the benefits by using human resources. Therefore, when considering the allocation of human resources, it is necessary to comprehensively consider the output value and profit generated by the completed workload. So the department's production efficiency data needs to include the output value and profit created by the department's human resources. Of course, the higher the efficiency obtained for the output value and profit, the better the utilization rate of human resources or the work efficiency of personnel. This kind of indirect reflection of human resources more quantitatively determines the current situation of the department's human resources and is the data basis for subsequent human resource requirement analysis.

[0040] Extract the production task volume information from the department's periodic production efficiency data, and conduct an analysis of the change in task volume to form the department's periodic task volume change data, including: determining the data volume processed within different production efficiency analysis periods to form the department's periodic task data volume; arranging the department's periodic task data volume in chronological order to form the task volume periodic change data.

[0041] Workload is the basis of the efficiency of human resources operations. Therefore, it is considered to obtain the workload of the operations first. Here, two aspects are considered for the quantification of workload. On the one hand, it is about how to reasonably quantify the workload in a proper way. On the other hand, since the workload of the department is continuous, it is about how to conduct reasonable quantitative analysis in the time dimension to make the analysis feasible. Here, for the quantification of workload, it is adopted to reflect the amount of data to be formed by the work tasks. After all, for workload, different types of work and the same operation content will have different forms of work content. Considering that under the Internet of Things, the operation data can be collected efficiently and accurately, and then obtaining the data volume corresponding to the workload has a good quantification manifestation. For the feasibility of quantitative analysis, it is considered that the analysis of human resources requirements is a data closely related to time parameters. Therefore, the quantification of workload also needs to be based on the time dimension. At the same time, the acquisition of workload has a certain degree of task periodicity, that is, under the project tasks, the workload has a certain definite value, and the completion of project tasks also has periodicity. Therefore, quantifying the task volume periodically based on the cycle characteristics of project tasks is conducive to subsequent analysis and processing. Of course, since the cycle times presented by different task projects are not highly consistent, reasonable cycle duration determination based on the actual situation is also required during periodic division to ensure more reasonable workload division or to avoid unreasonable splitting of work tasks based on task workload.

[0042] Extract the production output value information from the department cycle production efficiency data, and conduct production output value efficiency analysis to form department cycle production output value efficiency data, including: taking the project as a unit, determining the project output value of different projects in the department cycle production efficiency data According to the department cycle task data volume, determine the project task data volume q of different projects within the corresponding production efficiency analysis cycle n and the total project task data volume of different projects n represents the numbers of different projects within the production efficiency analysis cycle; according to the project output value of different projects corresponding to the production efficiency analysis cycle project task data volume q n and the total project task data volume determine the department cycle production output value q corresponding to the production efficiency analysis cycle all , where Arrange the department cycle production output value q in the order of time dimension all , and conduct function fitting to form the department cycle production output value change function Q(t).

[0043] The output value efficiency mainly reflects the amount of output value achieved by a department in relation to the human resources expended. Since the output value is corresponding to each task, it is reasonable and accurate to analyze the output value efficiency based on tasks over different cycles. Considering that not all tasks can be completed within the corresponding production efficiency analysis cycle, it is necessary to reasonably determine the workload within each production efficiency cycle, especially the workload formed by the department on different projects, so as to accurately determine the overall output value obtained within the cycle based on the project output value.

[0044] Extract the production profit information from the department's periodic production efficiency data and conduct profit efficiency analysis to form the department's periodic profit efficiency data, including: taking the project as the unit, determining the project profit of different projects in the department's periodic production efficiency data According to the project profit of different projects corresponding to the production efficiency analysis cycle The project task data volume q n And the total project task data Determine the department's periodic profit k corresponding to the production efficiency analysis cycle all , where Arrange the department's periodic profit k in chronological order all , and conduct function fitting to form the department's periodic profit change function K(t).

[0045] Similarly, for the production profit efficiency, it is also determined based on the profit obtained corresponding to the workload completed within the production cycle, in order to more reasonably and accurately reflect the revenue generation situation of the department in utilizing human resources.

[0046] S2: Collect the department's historical human resource data and conduct human efficiency analysis to form the department's current human efficiency data.

[0047] Collect the department's historical human resource data and conduct human efficiency analysis to form the department's current human efficiency data, including: setting the human efficiency analysis cycle, extracting the data volume completion rates of different humans on different projects in the department's historical human resource data; according to the data volume completion rates of different humans on different projects, determine the average human production efficiency a of each human m , where m represents the numbers of different existing humans in the department.

[0048] It can be understood that for different operators, due to their own or other reasons, there will be differences in production efficiency. At the same time, for different projects, the difficulty level of the projects will also affect the operation efficiency of humans. Therefore, the work efficiency of humans can be accurately determined through the human data collected within the analysis cycle, and this determined value is the average operation efficiency of different humans, which is more representative and reasonable.

[0049] S3: Based on the department production efficiency data and the current manpower efficiency data of the department, conduct a manpower demand analysis to form manpower demand analysis data.

[0050] Based on the department production efficiency data and the current manpower efficiency data of the department, conduct a manpower demand analysis to form manpower demand analysis data, including: Based on the task volume periodic change data and the average production efficiency a of different manpowers m , conduct an apparent manpower demand analysis to form apparent manpower demand information; Based on the apparent manpower demand information, and in combination with the department periodic output value change function Q(t) and the department periodic profit change function K(t), conduct an essential manpower demand analysis to form essential manpower demand information.

[0051] After obtaining the operation efficiency of human resources and the output value efficiency and profit efficiency generated by the tasks carried out by the department, the matching analysis of human resources and the tasks to be completed can be carried out. Of course, the processing situation of the workload can naturally quickly determine the preliminary situation of human resources, and on this basis, through further analysis, the specific human resource demand situation can be determined.

[0052] Based on the task volume periodic change data and the average production efficiency a of different manpowers m , conduct an apparent manpower demand analysis to form apparent manpower demand information, including: Based on the average production efficiency a of different manpowers m and the cycle duration T of different production efficiency analysis cycles i , determine the department competent data volume corresponding to the production efficiency analysis cycle Among them, i represents the number of different production efficiency analysis cycles; Based on the department periodic task data volume and the corresponding department competent data volume corresponding to different production efficiency analysis cycles determine the apparent task data surplus corresponding to different production efficiency analysis cycles Set the apparent manpower demand cycle number threshold α, and based on different apparent task data surpluses Conduct the following apparent manpower demand analysis: If there are α production efficiency analysis cycles that are consecutive in the time dimension and all satisfy the corresponding apparent task data surplus is not less than the total production volume of the manpower with the smallest average production efficiency a m in the corresponding production efficiency analysis cycle, then form apparent manpower shortage information; If there are no α production efficiency analysis cycles that are consecutive in the time dimension and all satisfy the corresponding apparent task data surplus is not less than the total production volume of the manpower with the smallest average production efficiency a m in the corresponding production efficiency analysis cycle, then form apparent manpower sufficiency information.

[0053] The preliminary or apparent human resource demand situation mainly examines whether the current human resources in the department can complete the given task workload within the cycle. This is the primary condition for forming human resource demand. After all, only when the task operations cannot be completed within the specified time, additional human resources are needed for supplementation. Therefore, the difference between the task workload and the task volume that the overall manpower can complete represents the magnitude of human resource demand to a certain extent. This demand is judged by setting a reasonable threshold. After all, a temporary increase in task volume will not affect the current human resource allocation, so this special change in task workload needs to be excluded.

[0054] Based on the apparent human resource demand information, combined with the department's cycle output value change function Q(t) and the department's cycle profit change function K(t), the essential human resource demand analysis is carried out to form essential human resource demand information, including: when the apparent human resource demand information is apparent human resource shortage information, a trend synchronization range A is set, and the following essential human resource demand analysis is carried out according to the department's cycle output value change function q(t) and the department's cycle profit change function K(t): According to the department's cycle output value change function Q(t) and the department's cycle profit change function K(t), the non-effective conversion economy F(t) is determined, where F(t) = Q'(t) - K'(t), Q'(t) represents the derivative of the department's cycle output value change function Q(t) in the time dimension, and K'(t) represents the derivative of the department's cycle output value change function K(t) in the time dimension; if the non-effective conversion economy F(t) satisfies F(t) ∈ A, essential human resource shortage information is formed; if the non-effective conversion economy F(t) does not satisfy F(t) ∈ A, essential human resource sufficiency information is formed.

[0055] If the workload of tasks to be completed within the workload analysis period exceeds the total workload that all human resources in the department can handle, and also exceeds the workload of the human with the lowest work efficiency in the department, it indicates that the continuously excess task workload has reached or even exceeded the workload that a single human can complete. The current human resources cannot meet the increasing workload requirements. Therefore, it is necessary to increase human resources in essence. By determining the derivative of the difference between the output value efficiency and the profit efficiency, it can be analyzed whether the change in profit is consistent with the change in output value. If the change in profit is consistent with the change in output value, it means that the department can achieve good profit growth, so there is no shortage of human resources. In this case, the task workload within the period exceeding the workload that all humans in the department can complete only indicates that the optimization of task processing can be further carried out, that is, the reasonable allocation of human resources. This allocation can be reflected in the improvement of human processing efficiency or the optimization of task workload. Of course, if the change in profit is inconsistent with the change in output value, it means that no corresponding income is obtained in terms of benefits after investing human resources. Therefore, it can be considered that the lack of human resources causes the inability to complete the core content of the task. In this case, an increase in human resources is required.

[0056] S4: Obtain the dynamic human resource demand information of the department, and combine it with the human resource demand analysis data to establish the human resource demand data of the department.

[0057] Obtain the dynamic human resource demand information of the department, and combine it with the human resource demand analysis data to establish the human resource demand data of the department, including: when the essential human resource demand information is the essential human resource shortage information, obtain the dynamic human resource demand information of the department, extract the human resource ability information based on semantics, and form the human resource ability condition items; aggregate different human resource ability condition items to form the human resource demand condition set.

[0058] Of course, after determining the real human resource needs of the department, the human resource demand information of the department obtained based on the Internet of Things can accurately determine the type and quantity of human resources required by the department, and then form the human resource demand condition data for the department, providing a reasonable and accurate reference for recruiting human resources.

[0059] This application also provides an enterprise cost management system based on big data. The system is configured to: continuously obtain the department work task data, conduct the conversion rate analysis based on the output value and profit, and form the department production efficiency data; collect the department historical human resource data, and conduct the human resource efficiency analysis to form the existing human resource efficiency data of the department; according to the department production efficiency data and the existing human resource efficiency data of the department, conduct the human resource demand analysis to form the human resource demand analysis data; obtain the dynamic human resource demand information of the department, and combine it with the human resource demand analysis data to establish the human resource demand data of the department.

[0060] Through configuration, the system can obtain department work task data for analysis of the output value-profit conversion rate, and combine human efficiency data for optimization analysis of human resource requirements to complete an organic whole for the reasonable control and management of human resource requirements, greatly improving the efficiency and rationality of enterprise cost management through human resource management, effectively ensuring that the enterprise realizes cost management through reasonable control of human resources, and enabling the enterprise to achieve the effect of reasonable cost reduction and efficiency increase in human resources.

[0061] In summary, the beneficial effects of the enterprise cost management method and system based on big data provided by the embodiments of the present invention are as follows:

[0062] This method obtains the work task data of departments, extracts the efficiency data of departments in terms of output value and profit for the work task data, and at the same time determines the operation efficiency of different human resources by using the historical data of department human resources. On this basis, it conducts a matching analysis of the current human resource operation efficiency and the department output value and profit efficiency to determine the human resource requirements of the department, thereby providing a reasonable and accurate reference for the enterprise to carry out human resource planning for the department. At the same time, it conducts a reasonable demand analysis on the human resource requirements proposed by the department in real time, so that when carrying out human resource planning, it can more reasonably determine the specific requirements of the human resources needed. Compared with the traditional human resource requirement analysis, after combining the quantitative data related to human resources collected by big data, it can more accurately and reasonably determine the specific situation of human resource requirements, greatly optimizing and improving the matching degree of the enterprise in terms of human resource requirements, and enabling the enterprise to achieve the effect of cost reduction and efficiency increase in cost management through human resources.

[0063] Through configuration, the system can obtain department work task data for analysis of the output value-profit conversion rate, and combine human efficiency data for optimization analysis of human resource requirements to complete an organic whole for the reasonable control and management of human resource requirements, greatly improving the efficiency and rationality of enterprise cost management through human resource management, effectively ensuring that the enterprise realizes cost management through reasonable control of human resources, and enabling the enterprise to achieve the effect of reasonable cost reduction and efficiency increase in human resources.

[0064] In the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. If the information indicated by a certain piece of information is called the information to be indicated, then in the specific implementation process, there are many ways to indicate the information to be indicated. For example, but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated, etc. It is also possible to indirectly indicate the information to be indicated by indicating other information, where there is an association relationship between the other information and the information to be indicated. It is also possible to only indicate a part of the information to be indicated, while the other parts of the information to be indicated are known or pre-agreed. For example, it is also possible to use the arrangement order of each piece of information pre-agreed (such as stipulated in the protocol) to realize the indication of specific information, thereby reducing the indication overhead to a certain extent. At the same time, it is also possible to identify the common part of each piece of information and indicate it uniformly to reduce the indication overhead caused by separately indicating the same information.

[0065] In addition, the specific indication method can also be various existing indication methods, such as, but not limited to, the above-mentioned indication methods and their various combinations, etc. The specific details of various indication methods can refer to the prior art and will not be elaborated herein. As can be seen from the above, for example, when it is necessary to indicate multiple pieces of information of the same type, there may be a situation where the indication methods of different pieces of information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiments of the present application do not limit the selected indication method. In this way, the indication methods involved in the embodiments of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0066] It should be understood that the information to be indicated can be sent together as a whole, or can be divided into multiple sub-information and sent separately, and the sending periods and / or sending times of these sub-information can be the same or different. The specific sending method is not limited in the embodiments of the present application. Among them, the sending periods and / or sending times of these sub-information can be predefined, such as predefined according to the protocol, or can be configured by the sending device by sending configuration information to the receiving device.

[0067] "Predefined" or "pre-configured" can be implemented by pre-saving the corresponding code, table or other ways that can be used to indicate relevant information in the device. The embodiments of the present application do not limit its specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be separately provided, or can be integrated in the encoder or decoder, processor, or communication device. The one or more memories can also be partly separately provided and partly integrated in the decoder, processor, or communication device. The type of the memory can be any form of storage medium, which is not limited in the embodiments of the present application.

[0068] In the embodiments of the present application, the "protocol" may refer to a protocol family in the communication field, a standard protocol with a frame structure similar to that of a protocol family, or a related protocol applied to future communication systems. The embodiments of the present application do not make specific limitations thereto.

[0069] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if", and "when" all refer to the situation where the device will perform corresponding processing under certain objective circumstances, rather than limiting the time. It is not required that the device must have a judgment action during implementation, nor does it mean that there are other limitations.

[0070] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship. For example, A / B may represent A or B. The "and / or" in the embodiments of the present application is merely a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. Also, in the description of the embodiments of the present application, unless otherwise specified, "a plurality of" means two or more than two. "At least one (item)" or its similar expression refers to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b, or c may represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple. Additionally, for the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and roles. Those skilled in the art can understand that the words "first" and "second" do not limit the quantity and execution order, and the words "first" and "second" do not necessarily limit being different. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, using words such as "exemplary" or "for example" aims to present relevant concepts in a specific way for easy understanding.

[0071] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0072] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0073] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0074] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context.

[0075] In this application, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0076] It should be understood that in various embodiments of the present application, the order of the serial numbers of the above processes does not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0077] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0078] Those skilled in the art can clearly understand that for the sake of convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0079] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0080] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] In addition, the functional units in each embodiment of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0082] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0083] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for enterprise cost management based on big data, characterized in that: include: Continuously obtain departmental work task data, conduct conversion rate analysis based on output value and profit, and form departmental production efficiency data; Collect the department's historical human resources data and conduct human resources efficiency analysis to form the department's current human resources efficiency data; Conducting a manpower demand analysis based on the department's production efficiency data and the department's existing manpower efficiency data to generate manpower demand analysis data; Obtain departmental dynamic human resource demand information, and combine the human resource demand analysis data to establish departmental human resource demand data.

2. The enterprise cost management method based on big data according to claim 1 is characterized in that: The continuous acquisition of departmental work task data, the conversion rate analysis based on output value and profit, and the formation of departmental production efficiency data include: Set a production efficiency analysis cycle, continuously obtain the work task data of large departments within the production efficiency analysis cycle, and form departmental periodic production efficiency data; Extracting the production task volume information from the department's periodic production efficiency data, and performing task volume change analysis to form departmental periodic task volume change data; Extracting the production output value information from the departmental periodic production efficiency data, and performing output value efficiency analysis to form departmental periodic output value efficiency data; The production profit information in the departmental periodic production efficiency data is extracted, and a profit efficiency analysis is performed to form departmental periodic profit efficiency data.

3. The enterprise cost management method based on big data according to claim 2 is characterized in that: The extracting of production task volume information from the department periodic production efficiency data and performing task volume change analysis to form department periodic task volume change data includes: Determine the amount of data processed in different production efficiency analysis cycles to form the department's periodic task data volume; The periodic task data of the department are arranged in time dimension order to form periodic change data of task volume.

4. The enterprise cost management method based on big data according to claim 3 is characterized in that: The extracting of production output value information from the departmental periodic production efficiency data and performing output value efficiency analysis to form departmental periodic output value efficiency data includes: Determine the project output value of different projects in the department's periodic production efficiency data on a project basis According to the amount of departmental periodic task data, determine the amount of project task data q of different projects in the corresponding production efficiency analysis cycle n and the total amount of project task data for different projects n represents the number of different projects in the production efficiency analysis cycle; The project output value of different projects corresponding to the production efficiency analysis cycle The project task data volume q n And the total amount of project task data Determine the department cycle output value q corresponding to the production efficiency analysis cycle all ,in, Arrange the periodic output value of the department in time order all , and perform function fitting to form the departmental cyclical output value change function Q(t).

5. The enterprise cost management method based on big data according to claim 4 is characterized in that: The extracting of production profit information from the departmental periodic production efficiency data and performing profit efficiency analysis to form departmental periodic profit efficiency data includes: Determine the project profits of different projects in the department's periodic production efficiency data on a project basis The project profits of different projects corresponding to the production efficiency analysis cycle The project task data volume q n And the total amount of project task data Determine the department cycle profit k corresponding to the production efficiency analysis cycle all ,in, Arrange the departmental periodic profit k in time order all , and perform function fitting to form the departmental periodic profit change function K(t).

6. The enterprise cost management method based on big data according to claim 5 is characterized in that: The collection of historical human resource data of the department and the analysis of human resource efficiency to form the current human resource efficiency data of the department include: Set a human efficiency analysis cycle to extract the data completion rate of different human resources under different projects in the historical human resource data of the department; According to the completion rate of the data volume of different manpower in different projects, determine the average manpower production efficiency of each manpower a m , m represents the numbers of different existing human resources in the department.

7. The enterprise cost management method based on big data according to claim 6 is characterized in that: The manpower demand analysis is performed based on the department production efficiency data and the department existing manpower efficiency data to form manpower demand analysis data, including: According to the task volume periodic change data and the average production efficiency of different manpower a m , conduct apparent manpower demand analysis and form apparent manpower demand information; According to the apparent manpower demand information, and in combination with the department periodic output value change function Q(t) and the department periodic profit change function K(t), an essential manpower demand analysis is performed to form the essential manpower demand information.

8. The enterprise cost management method based on big data according to claim 7 is characterized in that: The average productivity a of the manpower according to the task volume periodic variation data and different manpower m , conduct apparent manpower demand analysis and form apparent manpower demand information, including: According to the average productivity of different manpower a m and the cycle length T of different production efficiency analysis cycles i , determine the amount of department competency data corresponding to the production efficiency analysis cycle in, i represents the number of different production efficiency analysis cycles; The amount of departmental periodic task data and the amount of departmental competency data corresponding to different production efficiency analysis cycles Determine the apparent task data margin corresponding to different production efficiency analysis cycles Set the apparent manpower demand cycle number threshold α, according to the different apparent task data margins Conduct the following apparent manpower demand analysis: If there are α consecutive production efficiency analysis cycles in the time dimension sequence that all satisfy the corresponding apparent task data margin Not less than the average productivity of manpower a m The total production volume of the minimum manpower in the corresponding production efficiency analysis period forms the apparent manpower shortage information; If there are no α consecutive production efficiency analysis cycles in the time dimension sequence that all satisfy the corresponding apparent task data margin Not less than the average productivity of manpower a m The total production volume of the minimum manpower within the corresponding production efficiency analysis period forms the apparent manpower sufficiency information.

9. The enterprise cost management method based on big data according to claim 8 is characterized in that: According to the apparent manpower demand information, combined with the department periodic output value change function Q(t) and the department periodic profit change function K(t), the essential manpower demand analysis is performed to form the essential manpower demand information, including: When the apparent manpower demand information is the apparent manpower shortage information, the trend synchronization range A is set, and the following essential manpower demand analysis is performed according to the department periodic output value change function Q(t) and the department periodic profit change function K(t): According to the departmental periodic output value change function Q(t) and the departmental periodic profit change function K(t), determine the ineffective conversion economy F(t), wherein F(t)=Q'(t)-K'(t), Q'(t) represents the derivative of the departmental periodic output value change function Q(t) in the time dimension, and K'(t) represents the derivative of the departmental periodic output value change function K(t) in the time dimension; If the ineffective conversion economy F(t) satisfies F(t)∈A, then essential labor shortage information is formed; If the ineffective conversion economy F(t) does not satisfy F(t)∈A, essential manpower sufficiency information is formed.

10. An enterprise cost management system based on big data, adopting the enterprise cost management based on big data according to any one of claims 1 to 9, characterized in that: is configured as: Continuously obtain departmental work task data, conduct conversion rate analysis based on output value and profit, and form departmental production efficiency data; Collect the department's historical human resources data and conduct human resources efficiency analysis to form the department's current human resources efficiency data; Conducting a manpower demand analysis based on the department's production efficiency data and the department's existing manpower efficiency data to generate manpower demand analysis data; Obtain departmental dynamic human resource demand information, and combine the human resource demand analysis data to establish departmental human resource demand data.

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